Autonomous driving paper index
A Review of Image and Point Cloud Fusion-Based 3D Object Detection for Autonomous Driving
One-line summary
With the application of multi-sensor fusion technologies in object detection, Self-driving automobiles have received more and more attention.
Engineering notes
Key topics: autonomous driving system, autonomous driving, self-driving, 3d object detection, object detection, lidar, point cloud, sensor fusion, multi-sensor fusion, perception. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
With the application of multi-sensor fusion technologies in object detection, Self-driving automobiles have received more and more attention. The complementary advantages of different types of sensors (camera, LIDAR) can provide accurate and reliable environment perception for autonomous driving systems. We categorize the 3D object identification methods based on image and point cloud fusion into early, intermediate, and late, focusing on the camera and LIDAR combination in autonomous driving, furthermore, the characteristics of various methods and the performance of different models are analyzed and compared. Finally, the possible future opportunities and challenges for 3D object detection are evaluated.
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